An Empirical Analysis of the External Factor on Service Innovation - Based on SEM of Panel Data Set

2010 ◽  
Author(s):  
Yancai Zhang
Keyword(s):  
Panel Data ◽  
Empirical Analysis ◽  
External Factor ◽  
Service Innovation ◽  
Data Set

Focusing the High-Technology Firm: How Outsourcing Affects Technological Knowledge Exploration

2016 ◽  
Vol 44 (5) ◽  
pp. 1736-1765 ◽  
Author(s):  
Niron Hashai
Keyword(s):  
Panel Data ◽  
Empirical Analysis ◽  
High Technology ◽  
Technological Knowledge ◽  
Data Set ◽  
Technology Firms ◽  
High Technology Firms ◽  
Knowledge Exploration

This study argues and shows that the extent to which high-technology firms focus efforts by outsourcing production, assembly, and logistics activities enhances the extent of technological knowledge exploration. This occurs through three modalities: (1) intensifying the effect of internal R&D efforts on exploration; (2) intensifying the effect of learning from competing partners, through R&D alliances, on exploration; and (3) intensifying the effect of learning from customers on exploration. Empirical analysis of a panel data set of Israeli high-technology firms supports the view that the combination of these three modalities is associated with greater exploration of new technological knowledge.

Explaining Patterns of Broadband Development in OECD Countries

2011 ◽  
pp. 756-775
Author(s):  
Inmaculada Cava Ferreruela
Keyword(s):  
Panel Data ◽  
Empirical Analysis ◽  
New Technologies ◽  
Low Cost ◽  
Social Indicators ◽  
Oecd Countries ◽  
The Other ◽  
Data Set ◽  
Technological Competition ◽  
Key Drivers

The aim of this chapter is to provide some insights about the explaining patterns of broadband deployment and adoption. This problem is addressed by examining them in the light of the results of an exhaustive cross-national empirical analysis that uses a comprehensive panel data set from the 30 OECD countries with more than 40 features. The results suggest that technological competition and the low cost of deploying infrastructures on one side, and the predisposition to use new technologies as well as some social indicators on the other, appear to be the key drivers for broadband deployment and adoption, respectively.

State Rainy Day Funds and Government General Fund Expenditures: Revisiting the Stabilization Effect

2019 ◽  
Vol 47 (3) ◽  
pp. 465-492 ◽  
Author(s):  
Wenchi Wei ◽  
Dwight V. Denison
Keyword(s):  
Panel Data ◽  
Empirical Analysis ◽  
State Government ◽  
Explanatory Variable ◽  
Data Set ◽  
General Fund ◽  
Economic Recessions ◽  
Rainy Day Funds ◽  
Stabilization Effect ◽  
The Empirical Analysis

This study explores the stabilization effect of state rainy day funds (RDFs) on government general fund expenditures (GFEs). We discuss and explicitly illustrate the concept of stabilization effect. Moreover, we utilize the current year’s actual RDF usage as the explanatory variable of interest rather than the previous year’s RDF balance, which most existing studies focus on. A panel data set of states for fiscal years 1998 to 2014 is used in the empirical analysis. Due to the pro-cyclicality of the defined GFE gap and the countercyclicality of RDF usage, their positive correlation revealed in the empirical results demonstrates that the actual RDF usage helps to stabilize state government GFEs in both economic recessions and expansions. We also verify that the previous year’s RDF balance, when interacted with RDF deposit and withdrawal rules, can influence government GFEs, thus demonstrating the importance of RDF rules.

scholarly journals Does regulatory discretion increase the unofficial economy? Evidence from panel data

2015 ◽  
Vol 65 (1) ◽  
pp. 129-141
Author(s):  
Ummad Mazhar
Keyword(s):  
Panel Data ◽  
Empirical Analysis ◽  
Shadow Economy ◽  
Large Data ◽  
Causal Effects ◽  
Simple Correlation ◽  
Data Set ◽  
Large Data Set

One factor that contributes in the size of the shadow economy is the regulation of business activities. This paper provides empirical analysis of the effects of regulatory discretion on the unofficial economy. It adds to the previous findings by gathering evidence from a large data set of 162 countries for the 1999 to 2007 period. Going beyond simple correlation, it uses the Arellano-Bond estimator to investigate the dynamics and causal effects of regulation on the shadow economy. We find that increase in regulation increases the size of the shadow economy.

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